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Type 2 diabetes (T2D) is a multifactorial disease with substantial genetic risk, for which the underlying biological mechanisms are not fully understood. In this study, we identified multi-ancestry T2D genetic clusters by analyzing genetic data from diverse populations in 37 published T2D genome-wide association studies representing more than 1.4 million individuals. We implemented soft clustering with 650 T2D-associated genetic variants and 110 T2D-related traits, capturing known and novel T2D clusters with distinct cardiometabolic trait associations across two independent biobanks representing diverse genetic ancestral populations (African, n = 21,906; Admixed American, n = 14,410; East Asian, n =2,422; European, n = 90,093; and South Asian, n = 1,262). The 12 genetic clusters were enriched for specific single-cell regulatory regions. Several of the polygenic scores derived from the clusters differed in distribution among ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a body mass index (BMI) of 30 kg m-2 in the European subpopulation and 24.2 (22.9-25.5) kg m-2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg m-2 in the East Asian group. Thus, these multi-ancestry T2D genetic clusters encompass a broader range of biological mechanisms and provide preliminary insights to explain ancestry-associated differences in T2D risk profiles.

Established populations of Aedes aegypti, a mosquito vector of multiple major arthropod-borne viruses, were first found in three California (CA) cities in 2013. From 2013 to April 2021, Ae. aegypti thwarted almost all control efforts to stop its spread and expanded its range to 308 cities, including Exeter, in 22 counties in CA. Population genomic analyses have suggested that multiple genetically distinct Ae. aegypti populations were introduced into CA. However Ae. aegypti collected for the first time in 2014 in Exeter, appeared to be different from three major genetic clusters found elsewhere in CA. Due to intense control efforts by the Delta Vector Control District (DVCD), Ae. aegypti was thought to have been eliminated from Exeter in 2015. Unfortunately, it was recollected in 2018. It was not clear if the reemergence of Ae. aegypti in Exeter was derived from the bottlenecked remnants of the original 2014 Exeter population or from an independent invasion from a different population derived from surrounding areas. The goal of this work was to determine which of these scenarios occurred (recovery after bottleneck or reintroduction after elimination) and if elimination and reintroduction occurred to identify the origin of the invading population using a population genomic approach. Our results support the reintroduction after elimination hypothesis. The source of reintroduction, however, was unexpectedly from the southern CA cluster rather than from other two geographically closer central CA genetic clusters. We also conducted a knockdown resistance mutation profile, which showed Exeter 2014 had the lowest level of resistant alleles compared to the other populations, could have contributed towards DVCD’s ability to locally eliminate Ae. aegypti in 2014.

AIMS/HYPOTHESIS: Type 2 diabetes is highly polygenic and influenced by multiple biological pathways. Rapid expansion in the number of type 2 diabetes loci can be leveraged to identify such pathways. METHODS: We developed a high-throughput pipeline to enable clustering of type 2 diabetes loci based on variant-trait associations. Our pipeline extracted summary statistics from genome-wide association studies (GWAS) for type 2 diabetes and related traits to generate a matrix of 323 variants × 64 trait associations and applied Bayesian non-negative matrix factorisation (bNMF) to identify genetic components of type 2 diabetes. Epigenomic enrichment analysis was performed in 28 cell types and single pancreatic cells. We generated cluster-specific polygenic scores and performed regression analysis in an independent cohort (N=25,419) to assess for clinical relevance. RESULTS: We identified ten clusters of genetic loci, recapturing the five from our prior analysis as well as novel clusters related to beta cell dysfunction, pronounced insulin secretion, and levels of alkaline phosphatase, lipoprotein A and sex hormone-binding globulin. Four clusters related to mechanisms of insulin deficiency, five to insulin resistance and one had an unclear mechanism. The clusters displayed tissue-specific epigenomic enrichment, notably with the two beta cell clusters differentially enriched in functional and stressed pancreatic beta cell states. Additionally, cluster-specific polygenic scores were differentially associated with patient clinical characteristics and outcomes. The pipeline was applied to coronary artery disease and chronic kidney disease, identifying multiple overlapping clusters with type 2 diabetes. CONCLUSIONS/INTERPRETATION: Our approach stratifies type 2 diabetes loci into physiologically interpretable genetic clusters associated with distinct tissues and clinical outcomes. The pipeline allows for efficient updating as additional GWAS become available and can be readily applied to other conditions, facilitating clinical translation of GWAS findings. Software to perform this clustering pipeline is freely available.

Women and children in rural regions of low-income countries are exposed to high levels of household air pollution (HAP) as they traditionally tend to household chores such as cooking with biomass fuels. Early life exposure to air pollution is associated with aeroallergen sensitization and developing allergic diseases at older ages. This prospective cohort study assigned HAP-reducing chimney stoves to 557 households in rural Guatemala at different ages of the study children. The children's air pollution exposure was measured using personal CO diffusion tubes. Allergic outcomes at 4-5 years old were assessed using skin prick tests and International Study of Asthma and Allergies in Childhood (ISAAC)-based questionnaires. Children assigned to improved stoves before 6 months old had the lowest HAP exposure compared to the other groups. Longer exposure to the unimproved stoves was associated with higher risks of maternal-reported allergic asthma (OR = 2.42, 95% CI: 1.11-5.48) and rhinitis symptoms (OR = 2.01, 95% CI: 1.13-3.58). No significant association was found for sensitization to common allergens such as dust mites and cockroaches based on skin prick tests. Reducing HAP by improving biomass burning conditions might be beneficial in preventing allergic diseases among children in rural low-income populations.

BackgroundHundreds of thousands of biodigesters have been constructed in Nepal. These household-level systems use human and animal waste to produce clean-burning biogas used for cooking, which can reduce household air pollution from woodburning cookstoves and prevent respiratory illnesses. The biodigesters, typically operated by female caregivers, require the handling of animal waste, which may increase domestic fecal contamination, exposure to diarrheal pathogens, and the risk of enteric infections, especially among young children.ObjectiveWe estimated the effect of daily reported biogas cookstove use on incident diarrhea among children

The public health community has tried for decades to show, through evidence-based research, that safe water, sanitation, and hygiene (WASH) and clean cooking fuels that reduce household air pollution are essential to safeguard health and save lives in low-income and middle-income countries. In the past 40 decades, there have been many innovations in the development of low-cost and efficacious technologies for WASH and household air pollution, but many of these technologies have been associated with disappointing health outcomes, often because low-income households have either not adopted, or inconsistently adopted, these technologies. In this Viewpoint, we argue that public health researchers (ourselves included) have had an oversimplified understanding of poverty; our work has not focused on insights into the lived experience of poverty, with its uncertainties, stresses from constant scarcity, and attendant fears. Such insights are central to understanding why technologies for safe water or clean cooking are unused by so many households that could benefit from them. We argue that, rather than improved versions of household-scale delivery models, transformative investments in safe water and clean cooking for all require utility-scale service models. Until then, research should focus on interim safe water and clean cooking options that are directed towards the utility-scale service model.

BackgroundInadequate access to safe drinking water remains a global health problem, particularly in rural areas. Boiling is the most commonly used form of point-of-use household water treatment (HWT) globally, although the use of bottled water in low- and middle-income countries (LMICs) is increasing rapidly.ObjectivesWe assessed the regional and seasonal prevalence of HWT practices (including bottled water use) in low-income rural areas in two Chinese provinces, evaluated the microbiological safety of drinking water and associated health outcomes, and estimated the air pollution burden associated with the use of solid fuels for boiling.MethodsWe conducted cross-sectional surveys and collected drinking water samples from 1,033 rural households in Guangxi and Henan provinces. Temperature sensors affixed to pots and electric kettles were used to corroborate self-reported boiling frequencies and durations, which were used to model household air pollution (HAP) in terms of estimated particulate matter ≤2.5μm in aerodynamic diameter (PM2.5) concentrations.ResultsBased on summer data collection in both provinces, after controlling for covariates, boiling with electric kettles was associated with the largest log reduction in thermotolerant coliforms (TTCs) (-0.66 log10 TTC most probable number/100mL), followed by boiling with pots (-0.58), and bottled water use (-0.39); all were statistically significant (p

IntroductionHealth interventions often target pregnant women and their unborn children. Interventions in rural India targeting pregnant women, however, often do not cover the critical early windows of susceptibility during the first trimester and parts of the second trimester. This pilot seeks to determine if targeting newlyweds could protect entire pregnancies with a clean stove and fuel intervention.MethodsWe recruited 50 newlywed couples who use biomass as a cooking fuel into a clean cooking intervention that included a liquefied petroleum gas (LPG) stove, two gas cylinders, a table to place the stove on and health education. We first evaluated whether community health workers in this region could identify and recruit couples at marriage. We quantified how many additional days of pregnancy could be covered by an intervention if we recruited at marriage versus recruiting after detection of pregnancy.ResultsOn average, we identified and visited newlywed couples within 40 (SD 21) days of marriage. Of the 50 couples recruited, 25 pregnancies and 18 deliveries were identified during this 1-year study. Due to challenges securing fuel from the LPG supply system, not all couples received their intervention prior to pregnancy. Regardless, couples recruited in the marriage arm had substantially more days with the intervention than couples recruited into a similar arm recruited at pregnancy (211 SD 46 vs 120 SD 45). At scale, a stove intervention targeting new marriages would cover about twice as many weeks of first pregnancies as an intervention recruiting after detection of pregnancy.ConclusionsWe were able to recruit in early marriage using existing community health workers. Households recruited early in marriage had more days with clean fuel coverage than those recruited at pregnancy. Our findings indicate that recruitment at marriage is feasible and warrants further exploration for stove and other interventions targeting pregnancy-related outcomes.

St. Louis encephalitis virus (SLEV) is a flavivirus that circulates in an enzootic cycle between birds and mosquitoes and can also infect humans to cause febrile disease and sometimes encephalitis. Although SLEV is endemic to the United States, no activity was detected in California during the years 2004 through 2014, despite continuous surveillance in mosquitoes and sentinel chickens. In 2015, SLEV-positive mosquito pools were detected in Maricopa County, Arizona, concurrent with an outbreak of human SLEV disease. SLEV-positive mosquito pools were also detected in southeastern California and Nevada in summer 2015. From 2016 to 2018, SLEV was detected in mosquito pools throughout southern and central California, Oregon, Idaho, and Texas. To understand genetic relatedness and geographic dispersal of SLEV in the western United States since 2015, we sequenced four historical genomes (3 from California and 1 from Louisiana) and 26 contemporary SLEV genomes from mosquito pools from locations across the western US. Bayesian phylogeographic approaches were then applied to map the recent spread of SLEV. Three routes of SLEV dispersal in the western United States were identified: Arizona to southern California, Arizona to Central California, and Arizona to all locations east of the Sierra Nevada mountains. Given the topography of the Western United States, these routes may have been limited by mountain ranges that influence the movement of avian reservoirs and mosquito vectors, which probably represents the primary mechanism of SLEV dispersal. Our analysis detected repeated SLEV introductions from Arizona into southern California and limited evidence of year-to-year persistence of genomes of the same ancestry. By contrast, genetic tracing suggests that all SLEV activity since 2015 in central California is the result of a single persistent SLEV introduction. The identification of natural barriers that influence SLEV dispersal enhances our understanding of arbovirus ecology in the western United States and may also support regional public health agencies in implementing more targeted vector mitigation efforts to protect their communities more effectively.

Household air pollution from the combustion of biomass and coal is estimated to cause approximately 780,000 premature deaths a year in India. The government has responded by promoting uptake of liquefied petroleum gas (LPG) by tens of millions of poor rural families. Many poor households with new LPG stoves, however, continue to partially use traditional smoky chulhas. Our primary objective was to evaluate three strategies to transition pregnant women in rural Maharashtra to exclusive use of LPG for cooking. We also measured reductions in kitchen concentrations of PM2.5 before and after our interventions. Our core intervention was a free stove, 2 free LPG cylinders (one on loan until delivery), and repeated health messaging. We measured stove usage of both the traditional and intervention stoves until delivery. In households that received the core intervention, an average of 66% days had no indoor cooking on a chulha. In an adjacent area, we evaluated a conditional cash transfer (CCT) based on usage of LPG in addition to the core intervention. Results were less successful, due to challenges implementing the CCT. Pregnant women in a third nearby area received the core intervention plus a maximum of one 14.2 kg cylinder per month of free fuel. In their homes, 90% of days had no indoor cooking on a chulha. On average, exclusive LPG use decreased kitchen concentrations of PM2.5 by approximately 85% (from 520 to 72 μg/m3). 85% of participating households agreed to pay the deposit on the 2nd cylinder. This high purchase rate suggests they valued how the second cylinder permitted continuous LPG supply. A program to increase access to second cylinders may, thus, be a straightforward way to encourage use of clean fuels in rural areas.

Although access to piped drinking water continues to increase globally, information on the prevalence and clonal composition of coliforms found in piped water systems in low-resource settings remains limited. From June to July 2016, we examined Escherichia coli isolates in domestic water from the distribution system in Alibag, a small town in India. We analyzed the isolates for drug resistance and genotyped them by multilocus sequence typing. Of 147 water samples, 51 contained coliforms, and 19 (37%) of the 51 were biochemically confirmed to contain E. coli. These samples contained 104 E. coli isolates-all resistant to ampicillin. Resistance to ceftazidime was observed in 52 (50%) isolates, cefotaxime in 59 (57%), sulfamethoxazole-trimethoprim in 46 (44%), ciprofloxacin in 30 (29%), and gentamicin in two (2%). Thirty-eight (36%) belonged to sequence types recognized as extraintestinal pathogenic E. coli (ExPEC); 19 (50%) of these 38 ExPEC belonged to known uropathogenic E. coli lineages. This exploratory field research shows the extent to which "improved" drinking water is a potential source of E. coli strains capable of causing extraintestinal infections.

In Paraguay, 49% of the population depends on biomass (wood and charcoal) for cooking. Residential biomass burning is a major source of fine particulate matter (PM2.5 ) and carbon monoxide (CO) in and around the household environment. In July 2016, cross-sectional household air pollution sampling was conducted in 80 households in rural Paraguay. Time-integrated samples (24 hours) of PM2.5 and continuous CO concentrations were measured in kitchens that used wood, charcoal, liquefied petroleum gas (LPG), or electricity to cook. Qualitative and quantitative household-level variables were captured using questionnaires. The average PM2.5 concentration (μg/m3 ) was higher in kitchens that burned wood (741.7 ± 546.4) and charcoal (107.0 ± 68.6) than in kitchens where LPG (52.3 ± 18.9) or electricity (52.0 ± 14.8) was used. Likewise, the average CO concentration (ppm) was higher in kitchens that used wood (19.4 ± 12.6) and charcoal (7.6 ± 6.5) than in those that used LPG (0.5 ± 0.6) or electricity (0.4 ± 0.6). Multivariable linear regression was conducted to generate predictive models for indoor PM2.5 and CO concentrations (predicted R2  = 0.837 and 0.822, respectively). This study provides baseline indoor air quality data for Paraguay and presents a multivariate statistical approach that could be used in future research and intervention programs.

In 2017, the Joint Monitoring Programme estimated that 520 million people in India were defecating in the open every day. This is despite efforts made by the government, Non-Governmental Organizations (NGOs), and multilaterals to improve latrine coverage throughout India. We hypothesize that this might be because current interventions focus mostly on individual-level determinants, such as attitudes and beliefs, instead of considering all possible social determinants of latrine ownership. Given this, we ask two questions: what is the association between the amount of dwelling space owned by households in rural India and their likelihood of toilet ownership and what proportion of the variation in household latrine ownership is attributable to villages and states? We used multilevel modeling and found significant associations between the amount of household dwelling space and the likelihood of latrine ownership. Furthermore, considerable variation in latrine ownership is attributable to villages and states, suggesting that additional research is required to elucidate the contextual effects of villages and states on household latrine ownership. Thus, sanitation interventions should consider household dwelling space and village and state context as important social determinants of latrine ownership in rural India. Doing so could bolster progress towards Sustainable Development Goal (SDG) 6.

Approximately 3 billion people worldwide cook with solid fuels, such as wood, charcoal, and agricultural residues. These fuels, also used for residential heating, are often combusted in inefficient devices, producing carbonaceous emissions. Between 2.6 and 3.8 million premature deaths occur as a result of exposure to fine particulate matter from the resulting household air pollution (Health Effects Institute, 2018a; World Health Organization, 2018). Household air pollution also contributes to ambient air pollution; the magnitude of this contribution is uncertain. Here, we simulate the distribution of the two major health-damaging outdoor air pollutants (PM2:5 and O3) using state-of-thescience emissions databases and atmospheric chemical transport models to estimate the impact of household combustion on ambient air quality in India. The present study focuses on New Delhi and the SOMAARTH Demographic, Development, and Environmental Surveillance Site (DDESS) in the Palwal District of Haryana, located about 80 km south of New Delhi. The DDESS covers an approximate population of 200 000 within 52 villages. The emissions inventory used in the present study was prepared based on a national inventory in India (Sharma et al., 2015, 2016), an updated residential sector inventory prepared at the University of Illinois, updated cookstove emissions factors from Fleming et al. (2018b), and PM2:5 speciation from cooking fires from Jayarathne et al. (2018). Simulation of regional air quality was carried out using the US Environmental Protection Agency Community Multiscale Air Quality modeling system (CMAQ) in conjunction with the Weather Research and Forecasting modeling system (WRF) to simulate the meteorological inputs for CMAQ, and the global chemical transport model GEOS-Chem to generate concentrations on the boundary of the computational domain. Comparisons between observed and simulated O3 and PM2:5 levels are carried out to assess overall airborne levels and to estimate the contribution of household cooking emissions.

To tackle the severe fine particle (PM2.5) pollution in China, the government has implemented stringent control policies mainly on power plants, industry, and transportation since 2005, but estimates of the effectiveness of the policy and the temporal trends in health impacts are subject to large uncertainties. By adopting an integrated approach that combines chemical transport simulation, ambient/household exposure evaluation, and health-impact assessment, we find that the integrated population-weighted exposure to PM2.5 (IPWE) decreased by 47% (95% confidence interval, 37-55%) from 2005 [180 (146-219) μg/m3] to 2015 [96 (83-111) μg/m3]. Unexpectedly, 90% (86-93%) of such reduction is attributed to reduced household solid-fuel use, primarily resulting from rapid urbanization and improved incomes rather than specific control policies. The IPWE due to household fuels for both cooking and heating decreased, but the impact of cooking is significantly larger. The reduced household-related IPWE is estimated to avoid 0.40 (0.25-0.57) million premature deaths annually, accounting for 33% of the PM2.5-induced mortality in 2015. The IPWE would be further reduced by 63% (57-68%) if the remaining household solid fuels were replaced by clean fuels, which would avoid an additional 0.51 (0.40-0.64) million premature deaths. Such a transition to clean fuels, especially for heating, requires technology innovation and policy support to overcome the barriers of high cost of distribution systems, as is recently being attempted in the Beijing-Tianjin-Hebei area. We suggest that household-fuel use be more highly prioritized in national control policies, considering its effects on PM2.5 exposures.

The World Bank is publishing nine volumes of Disease Control Priorities, 3rd edition (DCP3) between 2015 and 2018. Volume 9, Improving Health and Reducing Poverty, summarises the main messages from all the volumes and contains cross-cutting analyses. This Review draws on all nine volumes to convey conclusions. The analysis in DCP3 is built around 21 essential packages that were developed in the nine volumes. Each essential package addresses the concerns of a major professional community (eg, child health or surgery) and contains a mix of intersectoral policies and health-sector interventions. 71 intersectoral prevention policies were identified in total, 29 of which are priorities for early introduction. Interventions within the health sector were grouped onto five platforms (population based, community level, health centre, first-level hospital, and referral hospital). DCP3 defines a model concept of essential universal health coverage (EUHC) with 218 interventions that provides a starting point for country-specific analysis of priorities. Assuming steady-state implementation by 2030, EUHC in lower-middle-income countries would reduce premature deaths by an estimated 4·2 million per year. Estimated total costs prove substantial: about 9·1% of (current) gross national income (GNI) in low-income countries and 5·2% of GNI in lower-middle-income countries. Financing provision of continuing intervention against chronic conditions accounts for about half of estimated incremental costs. For lower-middle-income countries, the mortality reduction from implementing the EUHC can only reach about half the mortality reduction in non-communicable diseases called for by the Sustainable Development Goals. Full achievement will require increased investment or sustained intersectoral action, and actions by finance ministries to tax smoking and polluting emissions and to reduce or eliminate (often large) subsidies on fossil fuels appear of central importance. DCP3 is intended to be a model starting point for analyses at the country level, but country-specific cost structures, epidemiological needs, and national priorities will generally lead to definitions of EUHC that differ from country to country and from the model in this Review. DCP3 is particularly relevant as achievement of EUHC relies increasingly on greater domestic finance, with global developmental assistance in health focusing more on global public goods. In addition to assessing effects on mortality, DCP3 looked at outcomes of EUHC not encompassed by the disability-adjusted life-year metric and related cost-effectiveness analyses. The other objectives included financial protection (potentially better provided upstream by keeping people out of the hospital rather than downstream by paying their hospital bills for them), stillbirths averted, palliative care, contraception, and child physical and intellectual growth. The first 1000 days after conception are highly important for child development, but the next 7000 days are likewise important and often neglected.

Exposure to household air pollution (HAP) from solid fuel combustion affects almost half of the world population. Adverse respiratory outcomes such as respiratory infections, impaired lung growth and chronic obstructive pulmonary disease have been linked to HAP exposure. Solid fuel smoke is a heterogeneous mixture of various gases and particulates. Cell culture and animal studies with controlled exposure conditions and genetic homogeneity provide important insights into HAP mechanisms. Impaired bacterial phagocytosis in exposed human alveolar macrophages possibly mediates several HAP-related health effects. Lung pathological findings in HAP-exposed individuals demonstrate greater small airways fibrosis and less emphysema compared with cigarette smokers. Field studies using questionnaires, air pollution monitoring and/or biomarkers are needed to better establish human risks. Some, but not all, studies suggest that improving cookstove efficiency or venting emissions may be associated with reduced respiratory symptoms, lung function decline in women and severe pneumonia in children. Current studies focus on fuel switching, stove technology replacements or upgrades and air filter devices. Several governments have initiated major programmes to accelerate the upgrade from solid fuels to clean fuels, particularly liquid petroleum gas, which provides research opportunities for the respiratory health community.

Emissions of airborne particles from biomass burning are a significant source of black carbon (BC) and brown carbon (BrC) in rural areas of developing countries where biomass is the predominant energy source for cooking and heating. This study explores the molecular composition of organic aerosols from household cooking emissions with a focus on identifying fuel-specific compounds and BrC chromophores. Traditional meals were prepared by a local cook with dung and brushwood-fueled cookstoves in a village in Palwal district, Haryana, India. Cooking was done in a village kitchen while controlling for variables including stove type, fuel moisture, and meal. Fine particulate matter (PM2.5) emissions were collected on filters, and then analyzed via nanospray desorption electrospray ionization-high-resolution mass spectrometry (nano-DESI-HRMS) and high-performance liquid chromatography-photodiode array-high-resolution mass spectrometry (HPLC-PDA-HRMS) techniques. The nano-DESI-HRMS analysis provided an inventory of numerous compounds present in the particle phase. Although several compounds observed in this study have been previously characterized using gas chromatography methods a majority of the species in the nano-DESI spectra were newly observed biomass burning compounds. Both the stove (chulha or angithi) and the fuel (brushwood or dung) affected the composition of organic aerosols. The geometric mean of the PM2.5 emission factor and the observed molecular complexity increased in the following order: brushwood-chulha (7.3±1.8 g kg-1 dry fuel, 93 compounds), dung-chulha (21.1±4.2 g kg-1 dry fuel, 212 compounds), and dung-angithi (29.8±11.5 g kg-1 dry fuel, 262 compounds). The mass-normalized absorption coefficient (MACbulk) for the organic-solvent extractable material for brushwood PM2.5 was 3.7±1.5 and 1.9±0.8m2 g-1 at 360 and 405 nm, respectively, which was approximately a factor of two higher than that for dung PM2.5. The HPLC-PDA-HRMS analysis showed that, regardless of fuel type, the main chromophores were CxHyOz lignin fragments. The main chromophores accounting for the higher MACbulk values of brushwood PM2.5 were C8H10O3 (tentatively assigned to syringol), nitrophenols C8H9NO4, and C10H10O3 (tentatively assigned to methoxycinnamic acid).

Air quality in rural India is impacted by residential cooking and heating with biomass fuels. In this study, emissions of CO, CO2, and 76 volatile organic compounds (VOCs) and fine particulate matter (PM2.5) were quantified to better understand the relationship between cook fire emissions and ambient ozone and secondary organic aerosol (SOA) formation. Cooking was carried out by a local cook, and traditional dishes were prepared on locally built chulha or angithi cookstoves using brushwood or dung fuels. Cook fire emissions were collected throughout the cooking event in a Kynar bag (VOCs) and on polytetrafluoroethylene (PTFE) filters (PM2.5). Gas samples were transferred from a Kynar bag to previously evacuated stainless-steel canisters and analyzed using gas chromatography coupled to flame ionization, electron capture, and mass spectrometry detectors. VOC emission factors were calculated from the measured mixing ratios using the carbon-balance method, which assumes that all carbon in the fuel is converted to CO2, CO, VOCs, and PM2.5 when the fuel is burned. Filter samples were weighed to calculate PM2.5 emission factors. Dung fuels and angithi cookstoves resulted in significantly higher emissions of most VOCs (p < 0.05). Utilizing dung-angithi cook fires resulted in twice as much of the measured VOCs compared to dung-chulha and 4 times as much as brushwood-chulha, with 84.0, 43.2, and 17.2g measured VOCkgg fuel carbon, respectively. This matches expectations, as the use of dung fuels and angithi cookstoves results in lower modified combustion efficiencies compared to brushwood fuels and chulha cookstoves. Alkynes and benzene were exceptions and had significantly higher emissions when cooking using a chulha as opposed to an angithi with dung fuel (for example, benzene emission factors were 3.18gkgg fuel carbon for dung-chulha and 2.38gkgg fuel carbon for dung-angithi). This study estimated that 3 times as much SOA and ozone in the maximum incremental reactivity (MIR) regime may be produced from dung-chulha as opposed to brushwood-chulha cook fires. Aromatic compounds dominated as SOA precursors from all types of cook fires, but benzene was responsible for the majority of SOA formation potential from all chulha cook fire VOCs, while substituted aromatics were more important for dung-angithi. Future studies should investigate benzene exposures from different stove and fuel combinations and model SOA formation from cook fire VOCs to verify public health and air quality impacts from cook fires.